The existence of strict compliance regulations and ethics laws in the banking and financial services industries compel companies to ensure the proper handling of documents. To optimize the high-volume information pulling of a big data model while ensuring compliance, firms utilize Optical Character Recognition (OCR). Given that a scanned document is simply a digital image of its original paper version, extracting information from scanned documents such as invoices requires time-consuming manual effort since the text is not machine readable. To automate text and data extraction, OCR technology must first be used to recognize the text and convert scanned documents into searchable PDFs.
Enabling Big Data Efficiency with Optical Character Recognition (OCR)
OCR enables the optimization of big data modeling by converting paper and scanned image documents to machine-readable, searchable PDF files. Processing and retrieving valuable information cannot be automated without first applying OCR in documents where text layers are not already present. With OCR text recognition, scanned documents can be integrated into a big data system that is now able to read client data from bank statements, contracts, and other important documents. Instead of having employees inefficiently examining countless image documents in an attempt to manually feed inputs into an automated big data processing workflow, organizations can use OCR to automate at the input stage of data mining, too.
Using OCR helps enterprises avoid time-consuming manual data retrieval, enabling employees to be re-purposed to contribute to the core operations of the firm. Before the financial organization The Debt Exchange began using our accurate OCR software, they relied on 20-25 employees working 8 hours a day to manually convert documents into searchable PDFs. Click here to read how 7 years of utilizing our efficient OCR text recognition technology has enabled the Debt Exchange to optimize their process of document conversion to machine-readable PDFs, saving the company time and money.
Additional Benefits of Digitizing Records in Banking and Financial Services
As financial entities that possess PII and sensitive data, banking and financial firms are subject to compliance regulations and evaluation by auditors. Consequently, firms need to efficiently and securely preserve financial records and archive documents. Manually sifting through thousands of paper documents to retrieve specific information is time-consuming and costly. The storage of paper documents is costly, as well. According to research done by PricewaterhouseCoopers, it costs an organization $20 on average to file a single document, roughly $120 to manually search for a misfiled document, and $220 to recreate a lost document.
The time and labor spent trying to find certain content throughout a plethora of documents is time that could have otherwise been allocated toward a firm’s core workflow. Our highly accurate OCR technology leverages expertise in image processing to reliably convert scanned documents from images into searchable PDF files, allowing for specific information retrieval with keyword search. Accordingly, banks and financial organizations are able to save on physical storage units costs and modernize by standardizing paper to digital document conversion.
In addition, our accurate OCR equips enterprises with the ability to standardize their document handling since scanned documents are now searchable PDFs rather than images saved as PDFs, PNGs, and so on. Using PDFs eliminates a company’s need to have multiple reader software solutions (and the systems in place to pay for, maintain, and train employees on those readers) to access the various different formats that a file can be saved as. Furthermore, using PDFs also decreases the amount of employees needed for information retrieval, lowering security risks.
Ready to test how efficiently our OCR technology integrates into your firm’s data mining to increase productivity? Begin your free trial of our highly accurate OCR software Maestro today!
